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   "cell_type": "markdown",
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   "source": [
    "# Churn Case Study\n",
    "\n",
    "## Introduction and Motivation\n",
    "<p>In this notebook we present an end-to-end analysis on a data mining task that is fairly common in the field. Most companies that provide subscription (whether free or not) services face the issue of customer churn. This is loosely defined as customers disengaging with the company's service, and in many cases, no longer paying for monthly or yearly fees. This issue is pervasive across industries (such as Telecom, Media, Music/Video Streaming, Gym Memberships, Credit Cards, Insurance, etc.), and it is common to find entire departments focusing on improving churn rates. \n",
    "\n",
    "<br><br>\n",
    "Churn reduction is a perfect environment for employing data mining techniques. Most companies maintain very detailed customer databases that host all of the data required to predict churn. An analysis of customer churn usually involves exploring the drivers of churn as well as predicting the likelihood. The goals are often multi-fold: on one level, predicting churn enables companies to proactively reach out to at-risk customers to prevent it. Additionally, understanding the drivers (re: causes) of churn gives valuable feedback for the company to improve the underlying product or service issues that may be causing customer dissatisfaction.\n",
    "\n",
    "<br><br>\n",
    "This notebook more than anything aims to illustrate a complete data mining workflow. Churn is the application but the emphasis here is on the steps one might take when perfoming a data mining task. There is Python code that generates the models and illustrations shown, but the emphasis here is more on the process than the code, so the code will mostly be hidden behind unexposed functions. We also provide generous discussion on how the results of the various analyses impact decisions one would make when focusing on churn reduction. \n",
    "</p>\n",
    "\n",
    "## Outline\n",
    "<p> Using a relatively straightforward churn dataset, we cover the following steps:\n",
    "<ul>\n",
    "    <li>1. Problem Formulation</li>\n",
    "    <li>2. Data understanding and exploration</li>\n",
    "    <li>3. Model building and model selection</li>\n",
    "    <li>4. Evaluation</li>\n",
    "    <li>5. Deployment</li>\n",
    "</ul>\n",
    "\n",
    "</p>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Problem Formulation\n",
    "<p>The first thing we should, as this guides the design of the entire analysis, is define the problem more formally. We know in general we want to reduce churn for the telecom firm. This could be implemented in several ways across the firm. \n",
    "<br>\n",
    "<ul>\n",
    "    <li>Proactively reach out to customers with a high likelihood of churn.</li>\n",
    "    <li>Create a reactive strategy, where we triage customers who call in based on their likelihood to churn.  </li>\n",
    "    <li>Study the data to gain insights into drivers of churn.</li>\n",
    "</ul>\n",
    "<br>\n",
    "The first two use cases suggest that we need to be able to rank customers based on their churn risk. Given that we have a binary outcome of interest, we know that we can apply some form of supervised learning to solve this problem. An important question is, do we want to only just rank, or do we want to rank and compute probabilities of churn? The answer here has implications over what type of supervised algorithm we will use. \n",
    "<br><br>\n",
    "For our specific task, we're going to choose an algorithm that can produce probabiliy estimates of churn risk for each customer. This should not restrict us in any way that prohibits us from exploring multiple classes of algorithms. Additionally, being able to esimate probabilities offers us greater flexibility in incorporate our models into calculating any expected value of applying various intervention strategies. So to put it more formally, our tasks will be the following:<br>\n",
    "<ul>\n",
    "    <li>1. Use available data to build a supervised learning algorithm that estimates the likelihood of churn, $P(Churn|X)$</li>\n",
    "    <li>2. Develop insights using the model and data to inform business constituents about drivers of churn  </li>\n",
    "    <li>3. Develop a framework for incorporating our probability estimates into one or more intervention strategies to reduce overall churn.</li>\n",
    "</ul>\n",
    "\n",
    "</p>\n",
    "\n",
    "\n",
    "## Data Exploration\n",
    "\n",
    "<p>The first thing one should do when starting an analysis is understand the data. \"Data understanding\" can represent multiple things of course. Here are some common questions to ask when approaching a data set:\n",
    "<br><br>\n",
    "<b>How was the data sampled, collected and aggregated?</b><br>\n",
    "Unless you planned and executed every step of the data sampling, logging and transformation processes, you should always spend some time exploring this question. The best analyses can be sabotaged by poorly sampled and logged data, so a data scientist always needs to understand what biases may exist in the data. The data for this churn analysis is comprised of all churners + a subset of non-churners, sampled so that there is a roughly even distribution between the two groups. Each sampled customer is represented by a vector of predictors $X = <X_1, X_2, ..., X_k>$ and an outcome $Y$. \n",
    "<br><br>\n",
    "When creating a dataset for churn modeling and analysis, one has to be mindful of the future application of the results. I.e., we don't want to predict <i>past</i> churn, we want to predict potential <i><b>future</b></i> churn. In building a data set to predict future churn, one can sample customers today and wait some period of time to observe whether or not the consumer churns. While this is technically accurate, you might not want to wait what could be weeks or months to start the analysis. Additionally, you might want to study several cohorts of sampled customers so your analysis isn't biased towards any time/seasonal dependent factors that are happening at the moment. The other option then is to simulate the future by going into the past. The following scheme shows how this is done:\n",
    "</p>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
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   "outputs": [
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2tfRRbTixdy3db204lbRmdB7eu/tQZ9JoQ4/Qvr+MVFq778TQRQ2fBD2N1BkO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\ne2Twqz07VwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image(filename='../references/churn_sampling_scheme.png') "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "<p>The point \"t = now\" is the day you're doing the analysis. We need to go back in time and create a virtual present, which we call $t=0$. We then look backwards to aggregate the predictor variables, and we look forwards in time to observe churn. The above represents one cohort, but this can be replicated across multiple cohorts (or multiple dates considered $t=0$ to either get access to more data or build dataset that has less dependency on any single seasonal effect). \n",
    "<br><br>\n",
    "\n",
    "<b>What are the variables in the dataset?</b><br>\n",
    "This is a simple question with a lot of implication behind it. Before digging into the distribution of the variables, one should first understand what they are from a domain perspective. Technically, you can build a model having no qualitative understanding of the data set. This works fine in homework assignments or data mining competitions. In industrial settings however, having the contextual and qualitative understanding of the data is generally critical to conducting an effective analysis, and even more critical in communicating and applying the results. The following links to a schema for the dataset we'll be using:\n",
    "<br><br>\n",
    "<a href=\"https://github.com/briandalessandro/DataScienceCourse/blob/master/ipython/references/churn_dataset_info.pdf\">Churn Data Schema</a>\n",
    "<br><br>\n",
    "Each of the independent predictor variables represents either some static demographic of the customer, or a summary of some aspect of the customer's usage of a cellular phone service (where the summary ends at time $t=0$).\n",
    "<br><br>\n",
    "An important question to highlight at this point is: <i><b>why are we using these specific variables?</b></i>\n",
    "<br><br>\n",
    "The implications of this question are often the difference between a decent model and a great model. Separate from the more technical topic of variable selection, is the topic of feature engineering (note: a \"variable\" and a \"feature\" are generally the same thing, but the more common phrase is \"feature engineering\"). The variables in this dataset were conceived and programmed by someone, and this part of the process is as much art as it is science. Most data infrastructure systems are designed to accommodate fast, production-level transaction processing. Analytics and modeling is often a secondary consideration. A data scientist is often responsible for pulling raw, log-level data from the transaction systems and designing the feature engineering pipelines that turn raw data into modeling variables. Designing the right variables requires domain knowledge of the system and insight into the behavior one is trying to predict. In this case, we'll assume that someone with deep knowledge of the problem has designed these specific variables with the hypothesis that these would both be effective predictors and scalable to create. Data scientists often find themselves working with pre-existing modeling systems. A very common research question is what new variables can be added to the existing set to improve prediction performance (note: we won't actually be covering this question in this case study)?  \n",
    "<br><br>\n",
    "<b>What does the data look like?</b><br>\n",
    "This is where we start to explore the data from a quantitative perspective. More formally, we want to gain an understanding of the joint distribution of $X$ and $Y$ (because this is ultimately a predictive modeling problem, we follow convention and label the dependent variable/outcome $Y$). We'll focus here on three aspects of the joint distribution: 1). descriptive statistics of each variable, 2). covariance of the predictors, 3). covariance of each predictor with the outcome. Within each aspect we'll cover implications of the results. \n",
    "</p>\n",
    "\n",
    "### Descriptive Statistics\n",
    "\n",
    "<p>The first thing we'll do is look at descriptive statistics of the data. Common statistics to look at are the mean, variance, range, and distribution (via the various quantiles of the distribution).\n",
    "\n",
    "</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>missing</th>\n",
       "      <th>distinct</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>revenue</th>\n",
       "      <td>58.633816</td>\n",
       "      <td>44.142467</td>\n",
       "      <td>-5.86</td>\n",
       "      <td>33.37</td>\n",
       "      <td>48.37</td>\n",
       "      <td>70.93</td>\n",
       "      <td>861.11</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11617.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>outcalls</th>\n",
       "      <td>24.874208</td>\n",
       "      <td>34.702038</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>13.00</td>\n",
       "      <td>33.33</td>\n",
       "      <td>610.33</td>\n",
       "      <td>0.0</td>\n",
       "      <td>738.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>incalls</th>\n",
       "      <td>8.011796</td>\n",
       "      <td>16.626837</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>8.67</td>\n",
       "      <td>519.33</td>\n",
       "      <td>0.0</td>\n",
       "      <td>434.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>months</th>\n",
       "      <td>18.789332</td>\n",
       "      <td>9.594723</td>\n",
       "      <td>6.00</td>\n",
       "      <td>11.00</td>\n",
       "      <td>16.00</td>\n",
       "      <td>24.00</td>\n",
       "      <td>61.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>56.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>eqpdays</th>\n",
       "      <td>391.935723</td>\n",
       "      <td>255.609575</td>\n",
       "      <td>-5.00</td>\n",
       "      <td>212.00</td>\n",
       "      <td>341.00</td>\n",
       "      <td>530.00</td>\n",
       "      <td>1823.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1396.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>webcap</th>\n",
       "      <td>0.895456</td>\n",
       "      <td>0.305968</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>marryyes</th>\n",
       "      <td>0.365338</td>\n",
       "      <td>0.481531</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>travel</th>\n",
       "      <td>0.057101</td>\n",
       "      <td>0.232039</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pcown</th>\n",
       "      <td>0.185378</td>\n",
       "      <td>0.388609</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>creditcd</th>\n",
       "      <td>0.675908</td>\n",
       "      <td>0.468041</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>retcalls</th>\n",
       "      <td>0.043955</td>\n",
       "      <td>0.224172</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>churndep</th>\n",
       "      <td>0.499285</td>\n",
       "      <td>0.500006</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from course_utils import *\n",
    "import churn_analysis as churn\n",
    "from IPython.display import display, HTML\n",
    "import importlib\n",
    "import numpy as np\n",
    "import eval_plots as val\n",
    "import os\n",
    "\n",
    "importlib.reload(churn)\n",
    "\n",
    "cwd = os.getcwd()\n",
    "datadir = '/'.join(cwd.split('/')[0:-1]) + '/data/'\n",
    "\n",
    "\n",
    "data = pd.read_csv(datadir + 'Cell2Cell_data.csv', header=0, sep=',')\n",
    "#Shuffle first\n",
    "data['r'] = np.random.random(data.shape[0]) \n",
    "data = data.sort_values(by = 'r').reset_index(drop = True)\n",
    "data = data.drop('r', 1)\n",
    "\n",
    "\n",
    "data_descr = churn.getDfSummary(data)\n",
    "HTML(data_descr.to_html())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "<p>Putting in tabular form is convenient and allows for easy comparison. The table here shows the descriptive statistics we discussed above, and also includes useful points such as count of missing values and the cardinality of the data. This last point is helpful for identifying which are binary variables. \n",
    "<br><br>\n",
    "<b>So what is the use of looking at this data?</b><br>\n",
    "Just glancing at the above, we can make the following observations of the data:\n",
    "<ul>\n",
    "    <li>The data contains no missing values. This is fortunate, but we're not always this lucky.</li>\n",
    "    <li>Two of the variables have records with negative values. There could be legitmate reasons for this, but intuitively this seems off and would be worth looking into. If discovered to be a data error, we may want to remove these records or replace the negative value with a more meaningful value.</li>\n",
    "    <li>The non-binary features are on different scales. This could be an issue with certain classification algorithms, and would require standardization prior to modeling.</li>\n",
    "    <li>Some of the variables (eqpdays, outcalls and incalls) are highly skewed (i.e., we see top quantiles and max that are much farther from the mean than the bottom quantile and min). If we need to use certain parametric classification algorithms (logistic regression, SVM), we may want to replace the existing variables with a few variable transformations (i.e., log(X), or binning).\n",
    "</ul>\n",
    "</p>\n",
    "\n",
    "### Variable Covariance\n",
    "<p>Another useful exploratory technique is to understand the correlation of the variables. If the dimensionality of the data is reasonable enough (a very subjective call admittedly), we can visualize the correlation matrix in a nicely intuitive way:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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zAAAAkzNsGwAAABgleQYAAGBiW9Z5nvZn7HWrHldVV1TVlVX1sh20+9Wq6qo6dhr3K3kG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\nqVQqH0J1niuVSqVSqVQqlUqlUvkQ/g/lRn/zRqwC/AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1800x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import importlib\n",
    "importlib.reload(churn)\n",
    "churn.plotCorr(data, 'churndep', 18, 8)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p>The above illustration let's us quickly see which variables have high degrees of correlation amongst themselves. In particular, we see that 'incalls' and 'outcalls' have alarmingly high correlation. Intuitively this might make sense, as someone who makes frequent calls would also be more likely to receive more calls. An important question of course is, does this matter? The answer of course (and this is the answer to many data science questions), is it depends. In general, we usually want to be cautious when several variables are highly correlated (and even more so if they are collinear). Certain supervised learning algorithms, such as tree-based algorithms, can automatically deal with highly correlated variables. Tree-based algorithms are particularly good at handling data 'as-is,' and one might choose to use them based on that property. However, many industrial systems are built around linear models, such as logistic regression. These algorithms are definitely sensitive to data irregularities, and can certainly give strange results when two or more features are highly correlated. <br><br>\n",
    "\n",
    "For the purpose of this case study, we're going to assume that we don't have restrictions on our choice of supervised learning algorithm. We can thus think ahead and acknowledge that our final model may likely be tree based, and as a consequence we won't explicitly correct for the high degree of correlation present here. If we wanted to though, some possible solutions could be simply dropping one of the correlated variables, or transforming the data using Principal Components. \n",
    "</p>\n",
    "\n",
    "### Targeted Exploration\n",
    "\n",
    "<p>Above we looked at how the various predictor variables correlated with each other. That is an exercise with its own motivation and implications. When faced with a supervised learning task, we often also care deeply about how all of the covariates correlate with our outcome of interest. This step of exploratory analysis has several benefits.<br>\n",
    "<ul>\n",
    "    <li><i><u>Pre-filtering of variables:</u></i>  In many cases we want to reduce the dimensionality of the dataset prior to modeling. In general, there is no sense in keeping variables that have no relationship with the outcome.  </li>\n",
    "    <li><i><u>Early insights:</u></i> We may want to report back progress to our business partners sooner than later. This step of the analysis will help us get early clues as to what are the primary drivers of churn.</li>\n",
    "</ul>\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'Mutual Information Between Variable X and Churn')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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xx7W57LLLtHXrVj399NM6evSojh49qk8//VRffvnlCbc7e/ZsdezYURMmTFCzZs30xBNP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\n9+zZY4cPH65XZ/GeyPr16+2uu+6yLl2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zc8ydO5f0ly39+asUFBRAT0+PpEcEmm9szczM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\noVAoH4EKZgqFQqFQKBQK5SP8P3S3vJEW3w/UAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "importlib.reload(churn)\n",
    "churn.plotMI(data, 'churndep', 0.4, signed=0)\n",
    "plt.title('Mutual Information Between Variable X and Churn')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p>This chart makes it pretty obvious which variables have a more correlated relationship with the churn outcome. For this analysis, we can ignore the absolute value of the mutual information and focus more on the relative values. Of the 11 variables, 3 look like they carry very little information about the Churn outcome. Of the remaining 8, 'revenue' clearly is the leader by far. This is interesting, but to truly interpret this, we need to know one more piece of information - does the variable in question have a positive or negative relationship with Churn? One issue with Mutual Information is that it doesn't tell us this piece. <br><br>\n",
    "\n",
    "With a little hacking, we can show the same plot but color the bars accoring to the direction of the correlation. \n",
    "</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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zWVmZJk2apBUrVigjI0OJiYnKyMio0GbhwoUKCgpSVlaWJk+erClTpkiSSktLNWbMGM2b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\nQqFQKBQKhUJ5C/8HIJAlTHv9QbsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "churn.plotMI(data, 'churndep', 0.4, 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p>The above chart shows Mutual Information, but with the bars colored according to the direction of the correlation. So to read this, we can say that as 'revenue' increases, the likelihood to churn goes down. We'll leave it as a thought experiment for the to do the following: \"How would you explain the qualitative implications of this chart to your marketing colleagues?\"\n",
    "</p>\n",
    "\n",
    "## Predictive Modeling\n",
    "\n",
    "### Setup\n",
    "\n",
    "<p>At this stage we should have a strong sense of where our data came from and what the data looks like. We know from our planning that we aim to learn a supervised model with a binary outcome. When we set up the problem, we set it up without specifying any specific constraints around the learning algorithm we can use. There are many industrial situations where one might only be able to choose from a small class of algorithms. This could be motivated by scalability concerns, legacy issues or regulatory mandates. <br><br>\n",
    "\n",
    "This is the stage where we need to decide whether or not to act on any of the data learnings we have observed above. We know we have at least one highly redundant feature as well as three features that seem to have no relationship with our outcome. If we were constrained to using a linear model like logistic regression, we would definitely want to consider dropping these variables. We know though that we have the allowance to use many more sophisticated tree-based algorithms, which conveniently enables us to just use the data as is. Nonetheless, we'll test in this study the effect of dropping these variables. \n",
    "</p>\n",
    "\n",
    "### Modeling Plan\n",
    "<p>Building the final model is one area where we can put the 'science' in data science. Specifically, choosing a model can be thought of as running a controlled experiment against the multitude of design options that can be built into modeling process. It generally helpful to be organized and specify the exact modeling options we will test. Here is the plan for this dataset:<br><br>\n",
    "\n",
    "<b>Modeling Design Parameters</b>\n",
    "<ul>\n",
    "    <li><b>Algorithms:</b> [Gradient Boosted Tree, Random Forest, Decision Tree, Logistic Regression]</li>\n",
    "    <li><b>Hyper-parameters:</b> Each algorithm has its own set of applicable hyper-parameters. We'll choose a grid of parameters that makes reasonable sense for each algorithm.</li>\n",
    "    <li><b>Variables:</b> All vs. All - {'incalls', 'creditcd', 'marryyes', 'travel', 'pcown'}</li>\n",
    "</ul><br>\n",
    "<b>Evaluation Plan</b><br><br>\n",
    "\n",
    "<u><i>Splits</i></u><br>\n",
    "You can't compare modeling options if you don't have a clearly articulated evaluation plan. We have a reasonably large dataset, with relatively few variables and balanced class distribution. We should consider ourselves spoiled (or at least lucky), that this is the case. The first decision we have to make is how to split the data. There is no time index, so we can just randomize across users. Because we have sufficient data, we would likely be fine creating three splits: training, validation, and testing. If we went this route, splits around 70%, 20%, 10% would likely do (remember, this particular decision is rather heuristic). \n",
    "<br><br>\n",
    "We don't have any particular constraints around modeling time, and the data isn't too large, so we'll go the extra mile and run cross-validation to do modeling selection. In cross-validation, we need a train/test split, and we can go 90%/10% for this. One advantage of cross-validation is that we can get variance estimates of our validation results, which gives flexibility in designing more conservative modeling selection rules. And on a practical note, we have to make sure we use the same exact cross-validation splits for each algorithm + hyper-parameter option. \n",
    "<br><br>\n",
    "\n",
    "<u><i>Evaluation Metric</i></u><br>\n",
    "Choosing the right evaluation metric is a critical decision whose importance is often overlooked. Specifically, we get to choose the evaluation metric used in validation. The training metric, which guides the empirical risk minimization algorithm in training, is often dicated by the algorithm (and is usually different for each algorithm).\n",
    "<br><br>\n",
    "The right metric should be guided by the application. Our example here has two potential applications: 1). to rank candidates according to likelihood to churn, and 2). to estimate good churn probabilities. The AUC would be an appropriate metric if we were just considering case (1), but we'll choose the LogLoss because of case (2). We'll discuss later how to create an expected value framework for putting our churn model into action. Before that though, we can say that a good churn probability estimator is a key element in computing expected values, and thus we'll choose the LogLoss.<br><br>\n",
    "\n",
    "<b>So now let's get onto the modeling!</b><br><br>\n",
    "\n",
    "Below is the most Python that we'll show in this case study. The code does a lot in just a few lines, and it shows pretty clearly the algorithms and hyper-parameters we're going to consider.\n",
    "</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#Here is the grid of hyper-parameters will test for each algorithm\n",
    "from sklearn.grid_search import GridSearchCV\n",
    "from sklearn.ensemble import GradientBoostingClassifier\n",
    "from sklearn.ensemble  import RandomForestClassifier\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.cross_validation import KFold\n",
    "\n",
    "\n",
    "models = {LogisticRegression():{'C':[10**i for i in range(-2, 5)], 'penalty':['l1', 'l2']},\n",
    "\n",
    "          GradientBoostingClassifier():{'learning_rate':[0.005, 0.01], 'n_estimators':[200, 500],\n",
    "                                      'max_depth':[3], 'subsample':[0.5]},\n",
    "\n",
    "          RandomForestClassifier():{'n_estimators':[200, 500, 1000], 'criterion':['entropy']},\n",
    "\n",
    "          DecisionTreeClassifier():{'min_samples_leaf':[20, 50, 100], 'criterion':['entropy']}}\n",
    "\n",
    "\n",
    "#1. Split the and prepare data\n",
    "\n",
    "train_all, test_all = trainTest(data, 0.9)\n",
    "train_subset = train_all.drop(['incalls', 'creditcd', 'marryyes', 'travel', 'pcown'], 1)\n",
    "test_subset = test_all.drop(['incalls', 'creditcd', 'marryyes', 'travel', 'pcown'], 1)\n",
    "\n",
    "kfolds = KFold(train_all.shape[0], n_folds = 4)\n",
    "\n",
    "\n",
    "#2. Start the model bakeoff \n",
    "\n",
    "best_models_all = {}\n",
    "best_models_sub = {}\n",
    "\n",
    "Y = 'churndep'\n",
    "\n",
    "\n",
    "for classifier in models:\n",
    "    \n",
    "    best_models_all[classifier] = GridSearchCV(classifier, models[classifier], cv = kfolds, scoring = 'log_loss') \n",
    "    best_models_sub[classifier] = GridSearchCV(classifier, models[classifier], cv = kfolds, scoring = 'log_loss') \n",
    "    \n",
    "    best_models_all[classifier].fit(train_all.drop(Y, 1), train_all[Y])     \n",
    "    best_models_sub[classifier].fit(train_subset.drop(Y, 1), train_subset[Y])\n",
    "    \n",
    "\n",
    "#3. We just need to save the summaries.  The actual GridSearchCV objects contain a lot of data that we don't need to keep in memory    \n",
    "summ_all = {}\n",
    "summ_set = {}\n",
    "\n",
    "for k in best_models_all:\n",
    "    summ_all[k] = [best_models_all[k].best_params_, best_models_all[k].grid_scores_]\n",
    "    summ_set[k] = [best_models_sub[k].best_params_, best_models_sub[k].grid_scores_]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p>Now let's plot the results of each algorithm against each other\n",
    "</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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kyJFyOBzWlp2drby8PHXs2LFWbdlsNqf98vJydezY0alu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qFDB3nttdeU/QkJCaLVaqV3796yf/9+OXz4sPj7+0u/fv2UNGvWrBErKyuJjY2VvLw8+eST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\n7hWO3bVrV1y7dk1hfwDA3r174ejoCJlMBjMzMwQHB+Ply5cK82dlZ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rnepk2biq5DiUSC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\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pkSNHqEuXLmRgYEANGzak3r17U1pamrB/27ZtpKmpSenp6ULarFmzyMLCgh48eFDtcZbJ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hYWhpSUFKxevRrHjx9HSEgIgoKCcPToUQDAN998g40bN2Lt2rU4e/YsEhIS4OnpCaBwipWL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RUlIS9u3btw9Pnz5FVFQULC0tMW7cOPj7+2PDhg3CLJOwsDAMGDAAy5Ytg7m5OZYtW4b+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\nRK5CYII=\n",
      "text/plain": [
       "<Figure size 1200x4800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "importlib.reload(churn)\n",
    "churn.plotGridSearchMulti([('All', summ_all), ('Sub', summ_set)], False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p>The above bar chart shows the cross-validation results of all algorithms tested and their respective hyper-parameter configurations. For convenience, we plotted two reference lines. The green line is just the LogLoss of our best classifier. The red line is the value of the best option plus 1 standard error of the mean of that option. The red line gives us the ability to choose a classifier using the 1-Standard Error rule, a generally good rule of thumb for being more conservative in one's selection. In our case here, the optimal option uses all of the data, but the option using the same algorithm and hyper-parmaters on less data is well within the 1-standard error here. When selecting a model, we generally want to promote parsimony (i.e., don't let things be more complex than they need to), so we'll go with the option that uses less data.  In the long-run, this could have multiple benefits: 1). cheaper to execute and maintain, 2). less over-fitting risk. <br><br>\n",
    "\n",
    "Now let us refit the model on the entire training set do evaluations on the test set.\n",
    "</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GradientBoostingClassifier(criterion='friedman_mse', init=None,\n",
       "              learning_rate=0.01, loss='deviance', max_depth=3,\n",
       "              max_features=None, max_leaf_nodes=None,\n",
       "              min_impurity_decrease=0.0, min_impurity_split=None,\n",
       "              min_samples_leaf=1, min_samples_split=2,\n",
       "              min_weight_fraction_leaf=0.0, n_estimators=500,\n",
       "              presort='auto', random_state=None, subsample=0.5, verbose=0,\n",
       "              warm_start=False)"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lab = 'churndep'\n",
    "best_model = GradientBoostingClassifier(n_estimators = 500, max_depth = 3, learning_rate = 0.01, subsample = 0.5)\n",
    "best_model.fit(train_subset.drop(lab, 1), train_subset[lab])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Evaluation\n",
    "<p>We discussed above that our core metric here will be LogLoss. This worked well for model selection, however, simply looking at the value of the LogLoss metric without any reference points isn't always helpful. Our main motivation for using LogLoss was that we ultimately want good estimates of churn probabilities. One tool for understanding how well we achieved this goal is the probability calibration plot. Our evaluation plan will be to start with calibration plots. For additional insight into our model capabilities, we'll also produce a lift chart. The lift chart is a good evaluation tool that is fairly accessible to non data scientists.\n",
    "\n",
    "\n",
    "</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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pmGZmZjh+/Di2bdtWYl1ISAhMTExKtMe9e/euUnv84ijFL/6UVtwCf7cthw8fxrlz5/D0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\n",
      "text/plain": [
       "<Figure size 1600x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import eval_plots as val\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "preds_train = best_model.predict_proba(train_subset.drop(lab,1))[:, 1]\n",
    "preds_test = best_model.predict_proba(test_subset.drop(lab,1))[:, 1]\n",
    "\n",
    "val.plotCalib(train_subset[lab].values.ravel(), preds_train, bins = 30, f = 4, l = 'Train', w = 16, h = 8, fig_i = 1, fig_j = 2, fig_k = 1)\n",
    "\n",
    "val.plotCalib(test_subset[lab].values.ravel(), preds_test, bins = 30, f = 4, l = 'Test', w = 16, h = 8, \n",
    "                fig_i = 1, fig_j = 2, fig_k = 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p>\n",
    "\n",
    "<i><b>Interpreting the calibration plots</b></i>\n",
    "<br><br>\n",
    "Remember, the point of the calibration plot is to understand whether or not our probability predictions actually result in probabilities that are near the prediction. Because we want to use our model predictions to estimate expected values, we want the calibration plot to be as close to the identity line as possible. Our main focus should be on the right chart above, which shows results for our out of sample dataset. The dominant trend we see here is that for the extremes (lower and higher estimated probabilities), our estimator tends to be more conservative. I.e., it underestimates the higher probabilities and overestimates the lower probabilities. We plot the 95% confidence intervals of the empirical probabilities (y-axis), and most of these overlap with the identity line. However, this might just be driven by sample size. We can see the same trend in the training, where the sample sizes are sufficient. <br><br>\n",
    "\n",
    "<i>What should we do about this?</i><br><br>\n",
    "\n",
    "When model calibration is an issue, we can deploy one of two tools to correct the problem. The first is a non-parametric method called Isotonic Regression, and the other is a parametric method called the Platt Correction. More details of these methods (in sklearn) can be found <a href=\"http://scikit-learn.org/stable/modules/calibration.html#calibration\">here</a>. Because our calibration error here is very mild, we'll hold off on running these corrections for now. This topic will be shelved in our 'further research' to-do list.  <br><br>\n",
    "\n",
    "We'll now make a secondary evaluation using lift and recall curves. These curves can help us answer other questions about our model, and they are generally accessible to non data scientists.\n",
    "\n",
    "</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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FTjnFwClJandlXb02BIYB18fImEaOPQOE7O4WwApgWoxc09Rzunpt5XvzTTjt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\nJEnSwNh0SpIkSZIG5n+kwF3EJgxnbAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1500x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lt = val.liftRecallCurve(pred = preds_train, truth = train_subset[lab].values.ravel(), b=50, h = 5, w = 15, \n",
    "                         title = 'Out of Sample Lift and Recall Curve for our Best Model')\n"
   ]
  },
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   "cell_type": "markdown",
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    "<p>\n",
    "\n",
    "<i><b>Interpreting the lift and recall plots</b></i>\n",
    "<br><br>\n",
    "These plots look pretty normal and they don't suggest any major hiccups or issues with our model. Apart from being diagnostic, they can help answer questions that might come up when we apply our model. For instance, if we wanted to design an intervention for the most at-risk churners, we'll of course need to choose a cut-off point. There are advanced ways to do this (we'll discuss this later), but one could be to reach out to the at-risk churners subject to some budget constraint. For instance, we might have a call center that can reach out to 20% of the customer base up for renewal. If we chose our cut-off as the top 20%, then with the recall plot we could see that we'd be reaching about 34% of the would be churners. Using the lift curve, we could say that this would make us about 36% more efficient at reaching would be churners than if we had just randomly reached out to people. \n",
    "</p>\n",
    "\n",
    "## Deployment\n",
    "\n",
    "<p>Since this is a case study motivated by a single, static dataset, we cannot actually deploy our churn prediction model. However, we can certainly consider how we might intend to put the model to use. There are many important considerations when deploying a prediction model in an industrial application. They two we'll discuss specifically are:\n",
    "\n",
    "<ul>\n",
    "    <li>How do we incorporate model output into a decision making framework?</li>\n",
    "    <li>How might we implement the model to support production level systems?</li>\n",
    "</ul>\n",
    "\n",
    "<br><br>\n",
    "<i><b>An Expected Value Framework for Churn Reduction</b></i>\n",
    "<br><br>\n",
    "The most important point to remember when doing data science is that a great prediction model doesn't alone solve our problem. Ultimately, the value we get from data and analytics comes from doing things differently because of that very data and analytics. One common way to use a model in churn reduction is to proactively reach out to at-risk customers with some form of an intervention strategy. Example interventions might include a personalized call from a customer service rep or an email with some targeted message. Beyond establishing a conversation with the customer, our interventions might likely include some special offer or discount that reduces the financial obligations of the customer. <br><br>\n",
    "\n",
    "It is pretty likely that any of our intervention strategies would come with some form of risk. Example costs that we might occur are: 1). the expense of calling someone from a call center, 2). annoying a user with too much email, 3). giving someone a discount or special offer when they indeed had no intention to churn. While all of these are important, the last point is likely the one that could have the biggest impact on overall revenues. We need to design a logical system here to choose when and when not to intervene. We can use expected values to design such a system. \n",
    "<br><br>\n",
    "The two main ingredients to our expected value formulation are the likelihood of the customer churning, and the expected lifetime value of the customer if (s)he should not churn. We'll call these $P(Y=1|X)$ and $E[LTV|X, Y=0]$. Note that we defined these conditional on the user attributes $X$, as this is how our churn prediction model is defined. Now let's define a variable $A \\in \\{0,1\\}$, where $A=1$ means we perform an intervention, and $A=0$ means we don't. <br><br>\n",
    "\n",
    "Our goal here is to maximize the expected lifetime value of each customer. For now, we have one decision lever - to intervene or not. From here, the decision apparatus is quite simple: intervene if doing so results in a higher expected value for the customer! In more formal terms, on each user with features $X=x$, intervene if:<br><br>\n",
    "\n",
    "<center>$(1 - P(Y=1|X=x, A=1))*E[LTV|X=x, Y=0, A=1] > (1 - P(Y=1|X=x, A=0))*E[LTV|X=x, Y=0, A=0]$</center>\n",
    "\n",
    "<br><br>\n",
    "Defining this decision rule both formally and informally is quite straightforward. Actually estimating it on the other hand is actually not at all straightforward. Our churn model (the focus of all of the above analysis), takes care of the quantity $P(Y=1|X, A=0)$, but will this estimate reflect churn probabilities if we decide to intervene? Sadly, the answer is likely no. To get an accurate estimate of $P(Y=1|X=x, A=1)$, we need to actually intervene on a set of users and test the effect of the intervention. This basically suggests we should design a controlled experiment and spend some resources collecting the appropriate data (see, the modeling is just one part of the process). <br><br>\n",
    "\n",
    "Additionally, we need to estimate accurate lifetime values (for now, we'll fold the cost of the intervention into the LTV). This is a highly non-trivial task, and doing it in a timely manner might require making many simplyfying assumptions. As this step is out of scope for this case study, we'll leave it as a discussion point. But for any reader deploying such a system in a real company, this is certainly a step that shouldn't be ignored.<br><br>\n",
    "\n",
    "\n",
    "<i><b>A Simple Production Scoring Architecture</b></i><br><br>\n",
    "\n",
    "Every deployed prediction modeling system has at least two components. These are the training module as well as the scoring module. Remember, it is through the application of the model that data and predictive analytics will add value, so the scoring system is critical to get right. Firms often have to make a decision whether or not to automate a modeling and scoring system. The right answer is ultimately company and project specific, but let's assume that for our company here we're interested in tackling the scoring system first. <br><br>\n",
    "\n",
    "Before writing any production code, we'll want to design a basic architecture for the system. In doing this, we'll want to specify the data dependencies, the data schemas and the process flows. We need to start by understanding and articulating our use cases. Given a working churn prediction model, we need a system that can support two cases: 1). periodically create lists of at-risk churners for proactive outreach, 2). look up churn risk for in-bound call center requests. An example of such an architecture is here:\n",
    "\n",
    "\n",
    "</p>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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uTJ6rvK/4GQRUBTcJpQqfEmkSfSE2LcEgKSSlLm0h4y2bKJe/7pJ8h8K4Ek5ZRGWDqqda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\njEV/yYK/UhXocWbpNeOEsG8kjtPQxjxbLVS3dUfuzL8/kjk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ULV++fNSoUQsXLmzbtm2D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\ndH+Wcc3bPAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(filename='../references/churn_scoring_architecture.png') "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p>Here is a quick description of each component in the above:<br>\n",
    "<ul>\n",
    "    <li>Activity Logs & User Info - These are the raw data systems that will ultimately be processed into modelable features</li>\n",
    "    <li>Feature Engineering Pipeline - This is the code that transforms raw log and data base information into structured model features. This pipeline should be identical to that used in the training phases</li>\n",
    "    <li>Churn Model DB - This is a data store that holds the actual prediction models (whether they be coefficients of a logistic regression, rules from a decision tree or python classifier objects)</li>\n",
    "    <li>Scoring Module - This module takes in structured features of a user and a model to produce a prediction.</li>\n",
    "    <li>User Churn Scores - This is a database that holds the most recently updated user churn prediction score.</li>\n",
    "</ul>\n",
    "<br>\n",
    "At this stage of implementation a lot of decisions will have to be made, such as, do we need to score users in real time or will some periodic batch update suffice? These are all application specific, but they do have implications for how the system and schemas are designed (not to mention what data storage systems will be used). <br><br>\n",
    "\n",
    "<i>Extending our system</i><br><br>\n",
    "\n",
    "Let's assume we're working for a truly agile company and we build things iteratively and as truly needed. Based on our research we had a working and validated model. Our first deployment project was to build the system that automatically scores users and stores the scores in a database. After a few successful months of using our system, we might decide that we need to update the prediction model. This is something that of course can always be done manually (repeating everything from above), but it is also worth considering building an automated system for doing so. This investment will ultimately free up research time for exploring new problems, or making the churn models even better. <br><br>\n",
    "\n",
    "Here is an example architecture where we extend the scoring system to include model updating. \n",
    "\n",
    "</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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xeE+UenXVr21dBlwOkX1wVapInn6VClAik4SJurJ2CjLEMKcXnXylRM5MSVPi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Rcc7Pd++cOtFx7zrSqIPLxu0it9cPLVN5acKAyAvef9bm9/t2bZx88Fdpq1Jx1e/DZ8/EJAYEhA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\nwFoqRC0ruHrwH2RpPbCeK78J1ZJzdHSyk1oqbK3tw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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(filename='../references/churn_architecture.png') "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p>This extension should be fairly cheap, as we have already built out the feature engineering pipeline that performs much of the data processing. One interesting implication of the above design is that we need to automate a lot of the decision making above that we originally did manually. This is out of the scope of this case study, but this is one of the most exciting areas of industrial data science research!\n",
    "\n",
    "\n",
    "</p>\n",
    "\n",
    "## Wrap Up\n",
    "\n",
    "<p>We have said a lot already, so this will be short! In this case study we tried to be thorough enough to cover all stages of defining, building and using a data science product in an industrial setting. Of course, an entire course can be taught on every element of this case study, so invariably, certain details have been left out. If you feel you have any suggestions on how to improve this case study, feel free to reach out at: briand at gmail dot com.\n",
    "\n",
    "</p>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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